NAVER LABS HD MAP DATASET

This dataset is a public large-scale HD map dataset for autonomous driving machines developed by NAVER LABS

Introduction
  • NAVER LABS has developed a full stack of autonomous technologies for urban autonomous driving. Among them, our own HD mapping and localization technologies are an indispensable component for ensuring safe autonomy. We have defined and built high definition (HD) maps of several complex urban areas in Korea and verified the practical usability of our HD maps for localization.

    NAVER LABS HD Map dataset is a public large-scale HD map dataset for autonomous driving machines developed by NAVER LABS. We open this dataset to the public in the hope that the development of autonomous driving technology will be accelerated through public research.

R1 - Mobile Mapping System

NAVER LABS R1 is a mobile mapping system (MMS) designed to create a high definition (HD) map for self-driving vehicles. As a comparatively lightweight MMS, R1 features a variety of sensors including multiple cameras, 2D & 3D LiDAR's, GPS, IMU, FOG and wheel encoders. Our map construction process integrates the sensor data obtained from R1 with 3D road layout information extracted from aerial photographs to create a hybrid HD map.

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Dataset
HD Map Dataset & Localization Dataset

NAVER LABS mapping technology is based on the integration of city-scale aerial photographs with data from a mobile mapping system. We extract information about the layout of the road surface (3D Road Layout) from aerial images. Then we integrate it with 3D point cloud collected by R1, our lightweight mobile mapping system (MMS). Compared to conventional HD maps constructed by MMS vehicles, our mapping process can significantly reduce the production costs and time. We also provide a separate localization dataset containing sensor data and pseudo ground truth poses which can be used for evaluation purposes.

More Information

HD Map Dataset

Our HD map dataset consists of three components: 1) 3D Road Layout - the types and locations of visual structures on the road surface such as lanes, road markings, crosswalks and speed bumps; 2) LiDAR Feature Data - 3D LiDAR point cloud of the static road environment captured from our MMS vehicle and semantic labels for each point; and 3) Visual Feature Data - visual features that are compact, discriminative and invariant across different viewing conditions, allowing for reliable matching and localization.

Localization Dataset

It is important to accurately estimate the current location of the vehicle in autonomous driving situations. The localization technology of NAVER LABS utilizes diverse sensors such as LiDAR, Cameras, GPS, IMU and Wheel Encoders. The localization dataset provides a collection of raw data from these sensors and corresponding pseudo ground truth poses for the purpose of evaluating your own localization algorithms. ​

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Explore Dataset

Please check out our HD Map & Localization (MMS) dataset.
Pangyo and Sangam datasets are now available!


Reference

Please check the following information before using the dataset.

Changelog

- UPDATE (2019.10.28) Dataset Released!

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Email: dl_hdmap@naverlabs.com
Copyright

All datasets on this page are copyrighted by NAVER LABS and published under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License. You must attribute the work in the manner specified by the author. You may not use the work for commercial purposes, and you may only distribute the resulting work under the same license if you alter, transform, or create the work.

Privacy

This dataset is for non-commercial use only. However, if you find yourself or your personal belongings in the data, please contact us, and we will immediately remove the respective images from our servers.